Neighborhood contexts can negatively impact alcohol outcomes, but few studies have examined how synergistic longitudinal interrelationships between neighborhoods, social networks and individual factors relate to relapse and recovery from alcohol problems. Lack of knowledge about these interrelationships over time limits our ability to design comprehensive prevention and treatment to address alcohol problems. To address significant gaps in the extant literature and inform service planning, this study will characterize healthy neighborhoods that inhibit relapse and support recovery. The study will also identify buffering factors amenable to intervention that can help prevent relapse by residents of high-risk neighborhoods. We propose to develop and test a socioecological model of relapse and recovery from alcohol problems to describe how neighborhood, social network and individual factors independently and interactively predict relapse and recovery from alcohol problems and dependence over time. The research aims are: (1) Describe county-wide distribution of treatment facilities, self-help resources and alcohol outlets relative to neighborhood socioeconomic resources, stability and disorder over time; (2) Examine longitudinal effects of these neighborhood characteristics on relapse, recovery, treatment utilization and self-help involvement; (3) Identify social network and individual factors that buffer or exacerbate neighborhood effects over time; and (4) Test whether there is a downward drift of problem drinkers into high-risk neighborhoods over time. The study uses data collected over 11 years from problem and dependent drinkers recruited from treatment centers (N=926) and the community (N=672) in a demographically diverse urban and rural county. Existing interview data will be linked with neighborhood indicators (including locations and characteristics of substance abuse treatment, self-help resources and alcohol outlets; socioeconomic resources; disorder and crime) via geocoded addresses at each interview. Analyses include neighborhood mapping and spatial random effects models, as well as multilevel longitudinal analysis, such as latent growth curve modeling and latent transition analysis. The study has several practical implications for relapse prevention, provision of formal substance abuse treatment and self-help, and policy pertaining to alcohol outlets. This innovative study will help prevent relapse by identifying specific neighborhood triggers that can be addressed during treatment. It also will identify modifiable factors, such as social network support for sobriety or participation in self-help that reduce negative consequences experienced by problem and dependent drinkers who live in high-risk neighborhoods, which could be addressed by treatment and prevention specialists. Ancillary programs also could be developed to facilitate housing changes by clients with limited financial resources to help them move from high-risk neighborhoods after treatment. Findings also will illustrate where alcohol outlets are especially detrimental and highlight where new treatment programs and self-help groups are needed.